BARRIERS TOWARDS THE ADOPTION OF MOBILE PAYMENT SERVICES - DIVA PORTAL
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Kathrin Dotzauer & Fabienne Haiss
Barriers towards the adoption of
mobile payment services
An empirical investigation of consumer resistance in
the context of Germany
Business Administration
Master’s Thesis
30 ECTS
Term: Spring 2017
Supervisor: Bertrand Pauget
Acknowledgements
We would like to thank our supervisor Bertrand Pauget for the support and
guidance throughout the process of this thesis. Furthermore, we would like to
sincerely thank all respondents participating in our survey as well as our
interview partners for sharing their knowledge with us.
Thank you all very much!
Karlstad, June 2017
Kathrin Dotzauer & Fabienne Haiss
II
Abstract
Purpose – Technological innovations continuously impact the daily routines
of consumers. In the case of mobile devices, their multifunctionality
revolutionizes possibilities for consumers, for example by conducting mobile
payments at a point of sale (proximity payments). Despite the advantages of
mobile payment services, the number of users of these services is very low
among German consumers. Therefore, the purpose of this paper is to examine
barriers which impede German consumers from adopting proximity mobile
payments by applying the theory of innovation resistance. More specifically,
this paper analyzes these obstacles regarding the usage barrier, value barrier, risk
barrier, tradition barrier, image barrier and the added information barrier.
Methodology – By utilizing a quantitative research approach with online self-
completion questionnaires, 152 answers from German consumers were
collected and statistically analyzed in order to empirically test the model of
innovation resistance. In addition, the characteristics age and smartphone
usage behavior of the participants were analyzed for examining further
characteristics of the consumers.
Findings – The results indicate that out of the examined six barriers, the
tradition, risk and value barrier have proven to be significant in influencing the
adoption intention of the questioned German consumers towards mobile
payment services. Additionally, a connection between the characteristics age
and smartphone usage behavior and the adoption intention could be detected.
Research implications – A key finding is that an innovation resistance
behavior among German consumers towards mobile payment exists according
to this study. This paper provides recommendations for service providers for
reducing the identified barriers and the consumer resistance for a successful
breakthrough of the innovation of mobile payment.
Originality/Contribution – This paper contributes to theory by applying the
less studied perspective of innovation resistance to the research field of mobile
payment, which is a novelty. Furthermore, insights into German consumers
were given helping service providers to develop effective marketing strategies
to meet the need of the consumers.
Keywords – Mobile payment, proximity mobile payment, innovation
resistance, adoption barriers, German consumers, smartphones
III
Table of Contents
Acknowledgements ........................................................................................... II
Abstract............................................................................................................ III
Table of Contents ............................................................................................. IV
List of Figures .................................................................................................. VI
List of Tables .................................................................................................... VI
List of Abbreviations ...................................................................................... VII
1. Introduction ................................................................................................ 1
1.1. Background & Problem discussion .............................................................. 2
1.2. Research gap ................................................................................................ 3
1.3. Research aims & Question ........................................................................... 4
1.4. Structure........................................................................................................ 5
2. Theoretical framework ............................................................................... 6
2.1. Mobile payment ............................................................................................ 6
2.1.1. Definition....................................................................................................................... 6
2.1.2. Prior research mobile payment .................................................................................. 8
2.2. Adoption barriers: Creation of innovation resistance ................................... 9
2.3. Innovation resistance model by Ram & Sheth (1989) ................................. 11
2.3.1. Usage barrier ............................................................................................................... 13
2.3.2. Value barrier ................................................................................................................ 13
2.3.3. Risk barrier .................................................................................................................. 13
2.3.4. Tradition barrier.......................................................................................................... 14
2.3.5. Image barrier ............................................................................................................... 14
2.3.6. Extensions and modifications of the model .......................................................... 15
2.4. Hypotheses development ........................................................................... 17
2.4.1. Hypothesis 1: Usage barrier ...................................................................................... 17
2.4.2. Hypothesis 2: Value barrier....................................................................................... 18
2.4.3. Hypothesis 3: Risk barrier ......................................................................................... 18
2.4.4. Hypothesis 4: Tradition barrier ................................................................................ 19
2.4.5. Hypothesis 5: Image barrier ...................................................................................... 19
2.4.6. Hypothesis 6: Information barrier ........................................................................... 20
2.5. Proposed conceptual framework ................................................................ 21
3. Methodology ............................................................................................. 22
3.1. Research strategy ........................................................................................ 22
3.2. Research design .......................................................................................... 23
3.3. Research method ........................................................................................ 24
3.3.1. Data collection method ............................................................................................. 24
3.3.2. Questionnaire design.................................................................................................. 25
3.3.3. Data analysis ................................................................................................................ 27
3.4. Validity & Reliability considerations.......................................................... 28
3.4.1. Validity ......................................................................................................................... 28
3.4.2. Reliability...................................................................................................................... 29
3.5. Ethical considerations ................................................................................ 29
3.6. Delimitations .............................................................................................. 29
IV
4. Results ...................................................................................................... 30
4.1. Descriptive analysis .................................................................................... 30
4.1.1. Demographics .............................................................................................................30
4.1.2. Additional information of participants ...................................................................32
4.1.3. Central tendencies.......................................................................................................33
4.2. Further analysis: Age and smartphone usage ............................................. 34
4.2.1. Age ................................................................................................................................34
4.2.2. Smartphone usage.......................................................................................................35
4.3. Scale measurement ..................................................................................... 36
4.3.1. Test for normality .......................................................................................................36
4.3.2. Reliability test: Cronbach’s alpha .............................................................................36
4.4. Inferential analysis ...................................................................................... 37
4.4.1. Pearson’s Correlation .................................................................................................37
4.4.2. Multiple regression .....................................................................................................39
4.5. Hypotheses testing ..................................................................................... 41
5. Discussion & Implications ....................................................................... 43
5.1. Innovation resistance model in the context of mobile payment ................ 43
5.1.1. Usage barrier................................................................................................................43
5.1.2. Value barrier ................................................................................................................44
5.1.3. Risk barrier...................................................................................................................45
5.1.4. Tradition barrier ..........................................................................................................45
5.1.5. Image barrier ...............................................................................................................47
5.1.6. Information barrier.....................................................................................................47
5.2. Theoretical implications ............................................................................. 48
5.3. Practical implications ................................................................................. 49
6. Conclusion ................................................................................................ 53
6.1. Limitations & Future research ................................................................... 55
References ........................................................................................................ 56
Appendix .......................................................................................................... 65
Appendix 1.1: Preliminary interviews ...................................................................... 65
Appendix 1.2: Interview partner .............................................................................. 67
Appendix 2: Summary of studies used for hypotheses development ...................... 68
Appendix 3: Questionnaire...................................................................................... 72
Appendix 4.1: SPSS output – Further analysis age .................................................. 76
Appendix 4.2: SPSS output – Further analysis smartphone usage.......................... 77
Appendix 5: Illustration of answers from the questionnaire ................................... 78
V
List of Figures
Figure 1: Classification mobile payment .............................................................................. 7
Figure 2: Summary of the relationship between innovations, resistance & adoption
barriers ....................................................................................................................................11
Figure 3: Summary of the innovation resistance model by Ram & Sheth (1989) .......12
Figure 4: Conceptual model for the study .........................................................................21
Figure 5: Gender distribution ..............................................................................................30
Figure 6: Age distribution ....................................................................................................31
Figure 7: Daily smartphone usage ......................................................................................32
Figure 8: Prior experiences with m-payment ....................................................................32
Figure 9: Updated conceptual framework .........................................................................42
Figure 10: Answers to question 11 – simplification of the payment process ..............78
Figure 11: Answers to question 12 – added value............................................................79
Figure 12: Answers to question 15 – abuse of data .........................................................79
Figure 13: Answers to question 16 – security of personal data......................................80
Figure 14: Answers to question 19 – preferred cash payments .....................................80
Figure 15: Answers to question 20 – image: insecurity of m-payments .......................81
Figure 16: Answers to question 26 – information overload ...........................................81
List of Tables
Table 1: Overview and definitions of the adoption barriers ..........................................16
Table 2: Number and type of questions for questionnaire .............................................26
Table 3: Means and standard deviations of items ............................................................33
Table 4: Smartphone usage differences .............................................................................35
Table 5: Kolmogorov-Smirnov Test ..................................................................................36
Table 6: Cronbach's alpha....................................................................................................37
Table 7: Pearson's Correlation ............................................................................................38
Table 8: Multiple regression – Fit of the model ...............................................................39
Table 9: Multiple regression – ANOVA............................................................................39
Table 10: Multiple regression – Coefficients ....................................................................40
Table 11: Hypotheses testing ..............................................................................................41
Table 12: Preliminary interview questions.........................................................................65
Table 13: Information about interview partner ................................................................67
Table 14: Overview of studies used for hypotheses development ................................68
Table 15: Questionnaire before and after pilot study ......................................................72
Table 16: Analysis – Age ......................................................................................................76
Table 17: Analysis – Smartphone usage ............................................................................77
VI
List of Abbreviations
AI Adoption intention
IB Image barrier
InfB Information barrier
M-payment Mobile payment
NFC Near Field Communication
POS Point of sale
RB Risk barrier
TB Tradition barrier
UB Usage barrier
VB Value barrier
VII
1. Introduction
The development of new technologies brings along endless possibilities for
new innovations impacting everyday lives. Especially in the field of mobile
commerce, the attention for innovations is growing globally (Oliveira et al.
2016). Smartphones do no longer only have the function to serve as a medium
to communicate but rather to operate as a multifunctional device enabling
consumers for example to perform all kinds of financial services via their
smartphones. The possibility to use smartphones or tablets for proximity
mobile payments, payments at a point-of-sale (POS) in a store (De Kerviler et
al. 2016), offers an alternative to cash or credit card.1 The innovation of
mobile payment (m-payment) revolutionizes these traditional payment
methods by utilizing wireless and other technologies of communication
(Dahlberg et al. 2015; Oliveira et al. 2016).
In addition, m-payment is supposed to bring along various advantages for all
the parties involved in the process. Especially for consumers m-payment
services offer a fast and simple alternative to cash while being secure and
facilitating purchase overview (Taylor 2016; Hayashi 2012). However, besides
the advantages of technological innovations, companies face a high number of
innovation failures (Kleijnen et al. 2009) which can be attributable to an
innovation resistance behavior of consumers. As a result, challenges and
barriers towards the acceptance of innovations appear which could count for
the German m-payment market. The source of the skepticism of German
consumers towards m-payment remains rather unexplored and therefore
needs to be examined more closely, especially when considering the size of the
German market. Germany does not only have the largest GDP amongst all
European countries but also holds the 4th position globally behind the US,
China and Japan (Knoema 2016). Furthermore, Germany has the highest
purchasing power in Europe (GTAI 2017). The importance of the mobile
economy in Germany is increasing. Therefore, it requires Germany to
continuously focus on what has put them in a leading economic position in
the world so far, which is the focus on knowledge and skills in technologies
and innovations (ibid).
1 The focus of this paper will be on proximity mobile payments which is abbreviated as m-payment in
the following sections.
1
1.1. Background & Problem discussion
The increasing number of smartphone users globally has an impact on the
development of mobile payment services in general (referring to remote- and
proximity mobile payments). While in 2014, 1.57 billion smartphone users
were reported worldwide, an increase to 2.87 billion users in 2020 is expected
(eMarketer 2016). The rise of the number of smartphones users goes along
with the increase of functions smartphones offer, facilitating the everyday life
of users, amongst others with the function of performing mobile payment
transactions. However, not only the worldwide number of smartphone users
in general increases, but also the number of users of m-payment services via
smartphones and tablets. The number of users of these services all over the
world amounted to 290 million in 2016 and is expected to rise to 663 million
users in 2021 (Statista 2016). Taking a more specific look at different
continents, one can say that the adoption intention of m-payment services
among users in Europe with 13% in 2016 is low compared to other regions
such as Asia/Pacific with 37% or Africa with 19% (Nielsen 2016). However,
the number of users in Europe are expected to increase as for example in
Germany it is expected to rise from 300.000 in 2016 to 6.1 million in 2021
(Statista 2016a).
Consequently, the transaction value is also forecasted to increase and play an
important role in the German payment market in the future. In Germany, the
transaction value of mobile payments in general amounted to US$15.7 million
in 2016 while the value is expected to have an annual growth rate of 85.1%
resulting in an expected transaction value of US$827 million in 2021 (Statista
2016a). There are various reasons explaining the increase in the number of
users and the transaction value of m-payment services in Germany in the near
future, one of them is the status quo of the m-payment market structure. The
main global players offering m-payment services at a POS are Samsung Pay,
Apple Pay and Android Pay amongst others (Gerstner 2016). However, none
of these key players has entered the German market so far, but plan to do so
soon (Richter 2017). Countries in Europe offering for instance Apple Pay are
to date only from France, Spain, the United Kingdom, Switzerland (Apple
2017) and Ireland (Rentrop 2017). In addition, in-store payment services
which are offered by Payback Pay seem to take a promising position as well
(UMT 2017). This means that the m-payment market in Germany is
considered to expand and develop significantly in the next years, as soon as
2
the key players will enter the market. Consequently, there is a high need for
knowledge about this market and its potential users.
Despite the auspicious numbers forecasting the development of the m-
payment market in general, m-payments at a POS are developing only
modestly, especially in Germany. As stated by Klotz2, this development can be
explained by the fact that m-payments can so far only be conducted in selected
supermarket chains and stores pointing to the early stage of this market.
Furthermore, it is crucial to consider the attitude of German consumers.
When it comes to the conduction of payments, Germans are supposed to be
traditional (ibi research 2015). The most frequently mean of payment is cash,
as 80% of the payments at a POS in Germany are made in cash making up
half of the total sales at a POS (Deutsche Bundesbank 2016). Especially minor
amounts are paid in cash (ibid.). The reason explaining this cash affinity is on
the one hand the perceived security of cash and on the other hand, the
simplicity when it comes to keeping an overview of expenditures (ibid). The
above explained structure of the market is also reflected in the number of
consumers of proximity mobile payments, as Germany is far behind other
European countries (Deloitte 2016). While people in Italy use their
smartphone for m-payments around 11% compared to 9% in the United
Kingdom and the Netherlands, Germany in contrast has the least number of
users with only 4% (ibid).
Therefore, it is of crucial importance to examine the reasons which prevent
German consumers from adopting m-payment services, particularly against
the background of the market entry of the aforementioned service providers
and the forecasted numbers. By studying the innovations resistance behavior
of German consumers, it will be possible to give recommendations for
lowering possible adoption barriers. In the end, marketing suggestions for
service providers will be made in order to boost adoption rates.
1.2. Research gap
Even though m-payments via smartphones are expected to gain popularity and
increase the number of users in the next years, there are challenges to
overcome.
First of all, it is important to mention the position of Germany when
comparing the number of users to other countries. In 2016, only 4% of the
2 Maik Klotz Senior Consultant KI Finance, interview on the 15th of March 2017.
3German population conducted m-payments at a POS (Deloitte 2016). The
reasons behind the low usage of German consumers for m-payment services
remain rather unexplored. Therefore, this paper aims to close this research gap
by examining the barriers hindering German consumers from using this
cashless payment method, as so far mainly research about the adoption
intention to m-payment exists with a focus on other markets (Dahlberg et al.
2015). In addition, academic research on German consumers remains scarce
(Khodawandi et al. 2003; Linck et al. 2006; Schierz et al. 2010).
Furthermore, to the knowledge of the authors, there is only one study
available examining three barriers to adoption of m-payment among American
university students (Pinchot et al. 2016). Therefore, this study takes this
different perspective by focusing on reasons behind the innovation resistance
behavior and thus on the barriers which impede German consumers from
adopting m-payments. For approaching this topic theoretically, models from
the innovation resistance theory examining the barriers to adoption will be
taken into consideration (Laukkanen 2016; Ram & Sheth 1989). Consequently,
the contribution of this thesis will be to apply the innovation resistance theory
to the research field of m-payment, which is a novelty. This way, this thesis
will contribute knowledge by providing strategical and marketing
recommendations for service providers to overcome obstacles consumers face
with m-payments.
Lastly, this thesis offers research on proximity mobile payments (De Kerviler
et al. 2016). As mobile payment can be understood as a general term
describing both remote and proximity payments (Dahlberg et al. 2015), it is
rather broad. However, by focusing on proximity m-payments at a POS, the
work conducted in this paper is of more specific use as recommendations can
be given more specifically. In addition, specifically this kind of payment have
so far shown the biggest obstacles in the adoption of consumers and is thus of
special interest (De Kerviler et al. 2016).
1.3. Research aims & Question
Resulting from the prior argumentations, the purpose of this research paper is
specified more precisely. The aim of this research is:
To examine the barriers which impede the adoption of proximity mobile payment services
among German consumers.
4More specifically, the following objectives will be covered in this research:
- Testing the theoretical model of Ram and Sheth (1989) in the context
of proximity mobile payments
- Verifying whether the added barrier to adoption which is the
“information barrier” is a valuable extension of the model
- Examining the influence of age and smartphone usage behavior
towards the adoption intention
- Demonstrating the consequences for services providers resulting from
the identified barriers
For addressing the aim and objectives, the following overarching research
question, which will be the baseline for reaching the subordinated objectives,
is developed:
Which barriers impede the adoption of German consumers to proximity mobile payment
services?
The purpose of this paper is to answer this question and meet the aim and
objectives during this research by consulting relevant literature as well as
collecting primary empirical data. For the specification of the research
question as well as for the objectives, preliminary interviews have been
conducted.3
1.4. Structure
The structure of this paper is as follows: the next chapter forms the theoretical
framework by describing the context of mobile payment, the theory of
innovation resistance dealing with the adoption barriers and prior research on
these topics. This is followed by the hypotheses development and the
conceptual model of this research, before chapter three covers the methodology.
In chapter four the results from collecting primary data are presented which are
analyzed and discussed in chapter 5 including theoretical and practical
implications. The conclusion as well as limitations and future research
possibilities complete this paper.
3Further information can be found in the method part 3.1 and in appendix 1.
Interview partner: Maik Klotz Senior Consultant KI Finance, interview on the 15th of March 2017;
Stefan Krüger VP GK Software AG, interview on the 16th of March 2017 & Klaus Steinkamp Head
Cashcloud SA, interview on the 23th of March 2017.
52. Theoretical framework
For the purpose of studying the barriers to adoption among German consumers, previous
research from the fields of mobile payment and innovation resistance is reviewed. This chapter
ends with the hypotheses development and the conceptual model of this study.
2.1. Mobile payment
2.1.1. Definition
According to Dahlberg et al. (2008), mobile payment is defined as:
Payments for goods, services, and bills with a mobile device (such as a mobile
phone, smart-phone or personal digital assistant (PDA)) by taking advantage
of wireless and other communication technologies. (Dahlberg et al. 2008,
p.165)
With this definition, Karnouskos (2004) adds that during a payment
transaction mobile devices have the task to confirm and authorize that a
financial value is exchanged for goods and services. Thus, what is new about
mobile payment compared to traditional payment methods is that, in this form
of transferring value the features of mobile devices are of importance and the
financial information of the consumers gets tokenized (Pandy & Crowe 2014).
It is a process between three different parties which are costumers, merchants
and banks (Ghezzi et al. 2010).
As displayed in figure 1, a distinction is drawn between remote and proximity
mobile payments for m-payment (Slade et al. 2013; De Kerviler et al. 2016).
Remote mobile payments are characterized as payments for digital content or
online purchases with the help of for instance a mobile internet connection.
Proximity mobile payments on the other hand, make payments for amongst others
ticketing or point-of-sale products possible. As already indicated in the name
of the technology, the main characteristic is the physical proximity, so the
close distance needed between the source of the payment and the one
receiving it (Ceipidor et al. 2012). The payment is transacted with either a QR-
code displayed on the smartphone, with a NFC (Near Field Communication)
equipped smartphone or via Bluetooth (Slade et al. 2013). With proximity
payments, the purchaser has to be on-site in person in order to receive the
product or service paid for (Kaymaz 2011).
6Figure 1: Classification mobile payment4
Proximity mobile payments can replace traditional in-store payment methods
as for example payments with cash, debit or credit cards (Dahlberg et al.
2008). The popularity and adoption of proximity m-payments is lower
compared to remote m-payments (De Kerviler et al. 2016) and will thus be in
the focus of this paper.
According to Hayashi (2012) proximity mobile payment services entail many
advantages for consumers. First of all, there is the advantage of portability since
card accounts can be collected and consequently, there is no longer the need
to carry several plastic cards (ibid). Another advantage is the speed of proximity
mobile payment since depending of the amount of a transaction, the consumer
only has to show or wave the smartphone in order to conduct the transaction
(ibid). Additionally, using proximity mobile payment can have cost saving
advantages since smartphones can connect certain promotions of stores to the
payments. Moreover, the management and controlling of finances is supposed
to be easier (ibid). Nonetheless, one of the greatest advantages is the high level
of security connected to m-payment transactions since the dynamic
authentications by the chip integrated in smartphones makes the data transfer
unique and does not refer to a static PIN (ibid).
4 Own representation based on Kaymaz (2011, p.25).
72.1.2. Prior research mobile payment
The research area of mobile payment in general is still in its beginnings
compared to related fields such as mobile commerce, internet banking or
mobile banking (Oliveira et al. 2016). However, the number of studies
increased significantly during the last years as between 2007 and 2014, 188
new articles were published (Dahlberg et al. 2015). This points to the
increasing importance and relevance of m-payment which corresponding
authors attribute to its potential to change the payment market (Hedman &
Henningsson 2015), its success in Asian countries (Miao & Jayakar 2016) and
its promising future as a technological innovation in general (Keramati et al.
2012; Oliveira et al. 2016).
The dominating research topics in the field of mobile payments up until today
are technology and consumer adoption of m-payments (Dahlberg et al. 2015).
This accumulation points to the importance of understanding the needs and
preferences of consumers in order to be able to offer a service which creates
value for consumers as well as for the whole ecosystem behind (Vargo &
Lusch 2016). However, Dahlberg et al. (2015) criticize in their literature review
that there is a need to explore new topics in m-payment research for enriching
the research field.
Furthermore, research studies conducted on German consumers are relatively
rare, but of relevance for this research as the focus is set on German
consumers. There only exist three scientific papers with slightly different
focuses. In 2003, Khodawandi et al. (2003) conducted a quantitative study
with 5110 participants on the acceptance of mobile payment procedures in
Germany. The main results indicate that security, convenience and cost are
rated as the most important criteria for the acceptance of mobile payment
services (ibid). In relation to the obviously high relevance of security issues
concerning m-payments, Linck et al. (2006) placed the focus of their study on
the dimensions of security of m-payments utilizing the empirical data set from
Khodawandi et al. (2003). Findings suggest that confidentiality is the most
important aspect of security concerns among German consumers (Linck et al.
2006) which indicates that m-payment service providers should pay attention
to confidentiality issues when marketing their services in Germany. However,
in contrast to these findings stands the research of Schierz et al. (2010) who
found out that perceived security and perceived ease of use (related to
convenience) are among the least important factors influencing German
consumers’ intention to use m-payment. According to Schierz et al. (2010)
8perceived compatibility, individual mobility and subjective norm are the most
relevant factors.
However, research specifically about proximity mobile payment is scarce (De
Kerviler et al. 2016). So far, the attention was mainly directed to the adoption
of remote-payment systems by applying different theoretical approaches (ibid).
However, amongst the few researchers having examined proximity mobile
payment De Kerviler et al. (2016) contributed by studying the key drivers
determining the adoption of consumers. Additionally, Slade et al. (2015)
discussed a new model of technology adoption aiming to explain effects
influencing the intention of non-users to adopt proximity mobile payments.
However, the study is limited to the NFC technology and the market of the
United Kingdom. The same limitations emerge for two other studies dealing
with proximity mobile payments. They focus on NFC payments and conduct
their study in Malaysia (Leong et al. 2013; Tan et al. 2014). Hence, so far
German consumers have not been in the focus of research about proximity
mobile payments.
2.2. Adoption barriers: Creation of innovation resistance
Throughout the literature, a multitude of research focusing on innovations can
be found, varying from companies’ perspectives of how to be innovative
through consumers’ acceptance of innovations. In general, the innovation
literature concentrates on the point of view that all innovations are good,
promise progress to consumers and emphasize the improvements over current
offers, thus postulating a pro-change bias (Kleijnen et al. 2009; Laukkanen et
al. 2007; Ram 1987). However, in practice companies have to face high
numbers of innovation failures (Kleijnen et al. 2009) of which one popular
example among numerous others is Coca-Cola. They introduced the “New
Coke” in 1985 for the purpose of replacing the old “Classic Coke” (The Coca-
Cola Company 2012). Coca-Cola had to face resistance from many consumers
and even protest groups were formed which in the end resulted in the
reintroduction of the “Classic Coke” (ibid).
This example illustrates that innovations also face resistance from consumers
preventing innovations from being successful, which has received much less
attention in academic research than innovation adoption (Chemingui & Ben
lallouna 2013; Claudy et al. 2015; Groß 2016; Heidenreich & Handrich 2015;
Laukkanen 2016). As innovations also always signify change to consumers,
resistance to this change is a normal human reaction (Laukkanen et al. 2007;
9Ram & Sheth 1989). More specifically, innovation resistance is defined by the
pioneers of innovation resistance research Ram and Sheth as:
The resistance offered by consumers to an innovation, either because it poses
potential changes from a satisfactory status quo or because it conflicts with
their belief structure. (Ram & Sheth 1989, p.6)
Bearing this in mind, it becomes clear that studying the reasons (barriers)
which prevent consumers from adopting innovations is of particular
importance as they need to be overcome before adoption can occur
(Laukkanen et al. 2008; Ram 1987). Focusing on barriers to adoption, also
affects the marketing of innovations as overcoming obstacles to decrease
resistance require different strategies than increasing the adoption of
innovations (Claudy et al. 2015; Kleijnen et al. 2009). For example, consumers
believe that mobile payments are more insecure compared to traditional
payment methods (Hayashi 2012). However, marketing strategies which solely
focus on the benefits of m-payment such as the factor of convenience, will fail
to convince consumers who are concerned with security issues as they will still
be in their minds. In consequence, it is of importance for companies to gain
knowledge about the barriers and reasons behind hindering consumers from
adopting innovations (Claudy 2011; Kleijnen et al. 2009).
For addressing this need, several prior studies have examined a consumer
resistance behavior, whereas the most popular research areas are internet and
mobile banking (e.g. Laukkanen et al. 2008; Laukkanen 2016) as well as online
and mobile shopping (e.g. Lian & Yen 2013; Groß 2016; Gupta & Arora
2017). The subject of mobile payment remains widely unexplored except for
the study of Pinchot et al. (2016). In their systematic literature review
Heidenreich and Handrich (2015) identified that there is a distinction between
active and passive innovation resistance. Active innovation resistance is formed
by consumers through specific product- or service-related attributes (ibid)
which implies that they decide to resist a concrete innovation due to certain
aspects of that innovation. In contrast to this, passive innovation resistance is a
more abstract term describing a general resistance towards innovations and
change which is not directly related to a product or service (ibid).
Since this paper focuses on the service of mobile payment, active innovation
resistance research will be taken into consideration. Active innovation
resistance is determined through functional and psychological barriers (see figure 2)5
5 The elements which are in the focus of this research are highlighted in figure 2.
10which had been conceptualized and investigated by several researchers (e.g.
Kleijnen et al. 2009; Laukkanen 2016; Ram & Sheth 1989).
Figure 2: Summary of the relationship between innovations, resistance & adoption barriers6
For illustrating the explanations of this paragraph, figure 2 summarizes the
relationships between innovations, innovation resistance, forms of innovation
resistance and the barriers to adoption.
2.3. Innovation resistance model by Ram & Sheth (1989)
The scholars Ram and Sheth (1989) were one of the first ones focusing their
research on barriers to adoption which create consumer resistance. They
presented a theoretical framework for studying innovation resistance. This
framework is the most utilized model in innovation resistance research and
has been continuously modified and tested in different contexts (Laukkanen &
Kiviniemi 2010). Although it is already quite old, the model is still relevant in
today’s research and especially suitable for this study as it has been applied in
several studies regarding technological innovations such as mobile banking or
online shopping (e.g. Antioco & Kleijnen 2010; Laukkanen 2016; Lian & Yen
2013). Further reasons for the suitability of this framework are that so far only
one study in the context of mobile payment focused on barriers to adoption
6Own representation based on findings of Heidenreich & Handrich (2015), Kleijnen et al. (2009) and
Ram & Sheth (1989).
11(Pinchot et al. 2016). However, they identified these barriers by analyzing
previous findings from adoption research and did not consider the concept of
innovation resistance. Therefore, this study will be the first one taking this
different perspective by systematically identifying barriers which impede
German consumers from adopting mobile payments with the help of the
theory of innovation resistance. Consequently, it was decided to rely on the
most proven and utilized framework of Ram and Sheth (1989).
Ram and Sheth (1989) determined five barriers to adoption which are
classified as functional barriers directly related to the innovation itself and
psychological barriers resulting from consumers’ conflicts with prior beliefs. The
functional barriers include three aspects which are usage patterns, value of the
product or service and risks associated when using the product or service
(ibid). Concerning psychological barriers, the authors identified that traditions
of consumers and the perceived image of innovations are most relevant. The
original model is summarized in figure 3.
Figure 3: Summary of the innovation resistance model by Ram & Sheth (1989)7
Although Ram and Sheth (1989) developed the concept theoretically, the five
identified barriers proved to be relevant and valid as several scholars tested
7 Own representation based on Ram & Sheth (1989).
12them in their empirical studies (e.g. Kuisma et al. 2007; Laukkanen et al. 2008;
Lian & Yen 2013).
2.3.1. Usage barrier
Innovations require consumers to change as new skills need to be learned and
existing habits need to be modified to be able to use a new product or service
(Ram & Sheth 1989). Especially in the beginning innovations require some
effort from consumers which can result in innovation resistance, particularly
when they are satisfied with their current situation and do not see a reason to
change (Kleijnen et al. 2009). The usage barrier (UB) refers to the functional
usability of an innovation, mainly including two aspects: The first one is
whether the new product or service is easy or difficult to use, whereas the
second one refers to the degree of change required from the consumers while
using the innovation which is mostly conflicting with habits (Laukkanen 2016).
2.3.2. Value barrier
The next barrier discusses the value the innovation provides to the consumer.
More specifically, Ram and Sheth (1989) referred to the innovation’s monetary
value and that the innovation needs to provide a convincing “performance-to-
price value” (Ram & Sheth 1989, p. 8) compared to alternatives. If the new
product or service implies higher efforts for consumers, it is likely that it will
face resistance. Applied in relation to mobile payments, this involves that
consumers perceive the efforts for utilizing m-payment services as being
higher than the benefits compared to traditional payment methods.
Additionally, other authors include in the value barrier (VB) the general
advantage or added value of utilizing an innovation compared to alternatives
(Laukkanen et al. 2008).
2.3.3. Risk barrier
With the changes innovations bring to consumers, also certain risks are
associated with them as new products or services contain several uncertainties
(Ram & Sheth 1989). Consumers being aware of risks are likely to resist
innovations. Following Ram and Sheth (1989) the risk barrier (RB) can be
divided into four risk types. The first one is physical risk describing that an
innovation can harm a person or a property (ibid). Transferred to
technological innovations this might contain concerns about privacy,
confidentiality and personal information (Chemingui & Ben lallouna 2013).
Secondly, economic risks are associated with the price paid for a new product or
13service which increases when the price is high (Ram & Sheth 1989). The next
type of risk is functional risk referred to the functionality of innovations and the
fear that as they are relatively new, do not function properly (ibid). One
example from mobile and internet banking is that consumers are especially
concerned with problems relating to internet connections (Chemingui & Ben
lallouna 2013) which could be relevant for m-payments. An additional aspect
of functional risks concerning m-payments, is the fear of being hacked while
conducting a payment at a POS as well as the fear of not having enough
power on the smartphone (Hayashi 2012). Finally, social risks describe the fear
of being judged from other people due to the utilization of a new product or
service (Ram & Sheth 1989). This last risk type was found to be less relevant
in the technology context (Kleijnen et al. 2009).
2.3.4. Tradition barrier
The tradition barrier (TB) is classified as a cause for psychological innovation
resistance and outlined by Ram and Sheth (1989) as an interference of long
established and valued routines. This barrier is especially important when it
comes to eating habits (Ram & Sheth 1989). However, it was also found to be
relevant in the context of technological innovations as for example when
utilizing self-service technologies with the absence of customary staff
members or the general fear of technology replacing human work (Chemingui
& Ben lallouna 2013). The greater the extent to which traditions are disrupted,
the greater is the resistance from consumers (Ram & Sheth 1989).
2.3.5. Image barrier
If an innovation is associated with unfavorable aspects of the manufacturing
brand, the country of origin or the industry, then consumers form a negative
image towards this innovation which is likely to result in resistance (Ram &
Sheth 1989). The image barrier (IB) is established uniquely through prejudices or
clichés and is therefore perceived individually (ibid). Regarding technological
innovations this aspect further involves a consumer’s general readiness
towards technologies or the belief that technologies are untrustworthy
(Laukkanen 2016). One example from mobile payment is that among many
consumers the image of not being a secure payment method was created
(Hayashi 2012). However, m-payment can significantly reduce misuses as
authentication is rather dynamic through for example NFC chips or facial
recognition (ibid). Compared to traditional payment methods where a static
14PIN or the same signature is used every time, this brings more security (ibid)
which is often not recognized by consumers.
2.3.6. Extensions and modifications of the model
Since the publication of the model in 1989, it has been continuously extended.
Concerning functional barriers, the barrier of complexity was added which occurs
when an innovation is hard to use or understand (Claudy 2011; Ram 1987;
Talke & Heidenreich 2014). However, these aspects are closely related to the
usage barrier from the original model (Laukkanen & Kiviniemi 2010) making it
unnecessary to include as an additional barrier.
Concerning psychological barriers, the information barrier (InfB) was found to be
relevant, emerging from a lack of information in relation to a new product or
service (ibid). When consumers feel that they do not know enough about an
innovation and do not receive help from the company offering the innovation,
they are likely to resist as it involves too much uncertainty (Kuisma et al.
2007). The information barrier could be important in the context of mobile
payments as market research institutes in Germany found out that consumers
do not use this new way of payment due to the reasons that they do not know
enough about it or that it is too difficult to receive relevant information
(eResult 2015; PwC 2016). In contrast to a lack of information causing
resistance, stand the recognitions of Kleijnen et al. (2009) who claim that
information overload, referring to the ever-increasing amounts of information
available in relation to new innovations, is increasing the resistance. Further,
the issue of information overload of consumers was problematized in the
expert interview.8 The barrier of information overload was examined by other
scholars as well, mainly in conceptual papers (Herbig & Day 1992; Herbig &
Kramer 1994; Hirschman 1987). The author Oreg (2006) hypothesized in a
quantitative research about employee’s resistance towards organizational
change, that more information about the change will reduce resistance.
However, the results indicated the opposite, meaning that less information
about the change decreases resistance (ibid). He concluded that the
relationship between resistance and information highly depends on the context
and should be examined more closely in future research. Therefore, it would
be beneficial to examine the barrier of information more thoroughly in this
research which will be elaborated more closely in the section of the hypotheses
development.
8 Stefan Krüger VP GK Software AG, interview on the 16th of March 2017.
15For a better overview, table 1 summarizes the barriers of the original model
and its extensions, relevant for this research.
Table 1: Overview and definitions of the adoption barriers
162.4. Hypotheses development
Derived from the literature reviewed in the previous sections, hypotheses can
be developed. The underlying theory which will be utilized is the innovation
resistance theory from Ram and Sheth (1989). Additionally, the InfB will be
added for a more comprehensive framework. Furthermore, the conducted
preliminary interviews were used to refine the hypotheses.9
2.4.1. Hypothesis 1: Usage barrier
The first barrier is the usage barrier. This barrier proved to have a strong
negative relationship to the adoption of innovations as detected in several
prior studies, especially in related contexts to m-payment such as mobile and
internet banking (Kuisma et al. 2007; Laukkanen et al. 2007; Laukkanen et al.
2008; Laukkanen 2016). Earlier studies on mobile banking suggested that
issues concerning the UB include the complexity of services, inconvenience,
slowness compared to other methods and authorization problems which all
prevented consumers from using the innovation (Chemingui & Ben lallouna
2013; Kuisma et al. 2007; Laukkanen 2016). All these attributes could be of
importance in relation to m-payment services. Furthermore, a critical question
is whether m-payment will be perceived to provide sufficient advantages over
existing payment methods concerning the handling of the service which was
also confirmed in the expert interview.10 Comparable to the UB is the notion
of ease-of-use from adoption research, where it was found that in the context
of m-payments, perceived ease-of-use has a significant positive influence on
the adoption (Keramati et al. 2012; Kim et al. 2010; Schierz et al. 2010).
Among German consumers, the aspects of getting rapidly familiar with the
service, few payment process steps and easy handling were found to be
important (Schierz et al. 2010). The prior findings show that if m-payment is
perceived as difficult to use, a UB will arise which will negatively impact the
adoption. Thus, the following hypothesis is developed:
H1: There is a negative relationship between the usage barrier and the
adoption intention of mobile payment.
9 A table with a summary of all studies used for formulating hypotheses can be found in appendix 2.
10 Maik Klotz Senior Consultant KI Finance, interview on the 15th of March 2017.
172.4.2. Hypothesis 2: Value barrier
The value barrier arises when consumers do not perceive m-payment to be
superior than existing payment methods. One of the main issues is the
question of the added value that m-payment provides over existing payment
methods which proved to be mainly unclear for German consumers as
detected by market research institutes (Deloitte 2016) and by the interviewed
experts.11 Evidence of the importance of the value aspect can be found in
adoption research in the comparable factor of perceived usefulness and
relative advantage (Daştan & Gürler 2016; Keramati et al. 2012; Kim et al.
2010; Pham & Ho 2015; Schierz et al. 2010). It was stated that if m-payment is
perceived to increase the flexibility and speed of payment for consumers, it
will positively influence the adoption (Daştan & Gürler 2016; Pham & Ho
2015). The aspect of speed is especially true for NFC payments in stores, as
consumers only need to wave their smartphones which proved to be 10-15
seconds faster than other payment methods (Pham & Ho 2015). However, in
case consumers do not know or value the benefits of m-payment, they are
likely to reject it. Previous literature from innovation resistance confirms that
the VB is one of the most significant impediments to adoption (Antioco &
Kleijnen 2010), especially in terms of online and mobile banking (Laukkanen
et al. 2007; Laukkanen 2016). Resulting from these finding, it can be
hypothesized that:
H2: There is a negative relationship between the value barrier and the
adoption intention of mobile payment.
2.4.3. Hypothesis 3: Risk barrier
Technological innovations are almost always perceived with risks, especially
when it comes to the sensitive topic of innovative payment methods which is
even more complex among German consumers. They are very concerned with
data protection, fraud and security issues, particularly regarding online services
(Dörner 2015) including m-payments (Khodawandi et al. 2003) which was also
confirmed in the expert interviews.12 The scholars Khodawandi et al. (2003)
and Linck et al. (2006) found out that perceived security risks are of crucial
importance for German consumers and emerged to one of the major
11 Maik Klotz Senior Consultant KI Finance, interview on the 15th of March 2017; Stefan Krüger VP
GK Software AG, interview on the 16th of March 2017 & Klaus Steinkamp Head Cashcloud SA,
interview on the 23th of March 2017.
12 Maik Klotz Senior Consultant KI Finance, interview on the 15 th of March 2017; Stefan Krüger VP
GK Software AG, interview on the 16th of March 2017.
18impediments to m-payment adoption. Furthermore, the RB includes concerns
about losing internet connection during a payment transaction, hacker attacks
or other abuse by third parties as for example abuse of usage information
(Kuisma et al. 2007; Laukkanen 2016; Schierz et al. 2010). Prior studies found
out that if the perceived risks are high, then it is likely that consumers will
resist the innovation. Thus, the following hypothesis is developed:
H3: There is a negative relationship between the risk barrier and the
adoption intention of mobile payment.
2.4.4. Hypothesis 4: Tradition barrier
Concerning the tradition barrier, the results of how tradition influences the
resistance varies among the research. According to the study from Chemingui
and Ben lallouna (2013) the TB was the largest inhibitor of adoption to mobile
financial services. This was confirmed in the expert interview underlining the
importance of traditional payment methods such as cash for German
consumers.13 However, in contrast to this is the findings of Antioco and
Kleijnen (2010) who identified that the TB reveals a positive influence on the
adoption of technologies characterized by low incompatibility and low
uncertainty. In adoption research the aspect of compatibility which resembles
the TB was found to positively influence the adoption when mobile payment
services were perceived to be compatible with existing values, experiences and
lifestyles (Schierz et al. 2010). Derived from prior findings that the TB has a
negative relationship on the adoption, the following hypothesis is developed:
H4: There is a negative relationship between the tradition barrier and
the adoption intention of mobile payment.
2.4.5. Hypothesis 5: Image barrier
Previous studies detected that the image barrier is of importance, as in the
research of Laukkanen (2016) it was found to be the second largest inhibitor
of the adoption of mobile banking. Furthermore, the image that the internet in
general is an insecure channel and is difficult to use, negatively influences the
adoption (Laukkanen et al. 2008). This is in line with the study findings of
Kuisma et al. (2007) that some consumers react negatively when services are
moved to the internet or in this case that services are moved to mobile
13 Maik Klotz Senior Consultant KI Finance, interview on the 15th of March 2017.
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